WEKA

Sudhir PawarBatch - IT 33-34

Introduction to WEKA

Waikato Environment for Knowledge Analysis It’s a data mining/machine learning tool developed

by Department of Computer Science, University of

Waikato, New Zealand.

Weka is also a bird found only on the islands of

New Zealand.

Software Platform : Java

Main Features

49 data preprocessing tools

76 classification/regression algorithms

8 clustering algorithms

3 algorithms for finding association rules

15 attribute/subset evaluators + 10 search

algorithms for feature selection

Installation

Website:

http://www.cs.waikato.ac.nz/~ml/weka/index.html

Support multiple platforms (written in java):

Windows, Mac OS X and Linux

WEKA has been installed in the teaching labs in

SEEM

WEKA Interfaces

Three graphical user interfaces

“The Explorer” (exploratory data analysis)

“The Experimenter” (experimental

environment)

“The Knowledge Flow” (new process model

inspired interface)

“Simple CLI”

WEKA GUI Interfaces

LOAD Filter

Analyze

WEKA Data Format

Data can be imported from a file in various formats: ARFF, CSV, C4.5, binary

Data can also be read from a URL or from an SQL database (using JDBC)

Pre-processing tools in WEKA are called “filters”

WEKA contains filters for: Discretization, normalization, resampling,

attribute selection, transforming and combining attributes, …

WEKA :: ARFF file format

@relation heart-disease-simplified

@attribute age numeric@attribute sex { female, male}@attribute chest_pain_type { typ_angina, asympt, non_anginal,

atyp_angina}@attribute cholesterol numeric@attribute exercise_induced_angina { no, yes}@attribute class { present, not_present}

@data63,male,typ_angina,233,no,not_present67,male,asympt,286,yes,present67,male,asympt,229,yes,present38,female,non_anginal,?,no,not_present...